gibbs sampling segmentation of parallel dependency trees for tree-based machine translation
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ID: 151927
2016
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Abstract
We present a work in progress aimed at extracting translation pairs of source and target dependency treelets to be used in a dependency-based machine translation system. We introduce a novel unsupervised method for parallel tree segmentation based on Gibbs sampling. Using the data from a Czech-English parallel treebank, we show that the procedure converges to a dictionary containing reasonably sized treelets; in some cases, the segmentation seems to have interesting linguistic interpretations.
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david2016praguegibbs
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| Authors | ;Mareček David;Žabokrtský Zdeněk |
| Journal | prague bulletin of mathematical linguistics |
| Year | 2016 |
| DOI |
10.1515/pralin-2016-0005
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